Update README.md
Browse files
README.md
CHANGED
|
@@ -8,61 +8,27 @@ tags:
|
|
| 8 |
- dataset_size:4615
|
| 9 |
- loss:TripletLoss
|
| 10 |
base_model: sentence-transformers/all-mpnet-base-v2
|
| 11 |
-
widget:
|
| 12 |
-
- source_sentence: Do you ever feel like you have failed in life or let yourself down?
|
| 13 |
-
sentences:
|
| 14 |
-
- But I just don't feel like even getting started because I know that I will fail
|
| 15 |
-
again.
|
| 16 |
-
- I cant remember the last time I felt happiness.
|
| 17 |
-
- That was their biggest and last mistake.
|
| 18 |
-
- source_sentence: Do you feel sad or unhappy?
|
| 19 |
-
sentences:
|
| 20 |
-
- I have been depressed since late September so I feel you.
|
| 21 |
-
- I share a lot of your traits, and considered myself a failure too.
|
| 22 |
-
- He conveys that feeling of regret so well I can feel it everytime
|
| 23 |
-
- source_sentence: Do you feel hopeful about your future or do things seem hopeless?
|
| 24 |
-
sentences:
|
| 25 |
-
- I'm pretty optimistic though since the pace of technological growth is accelerating
|
| 26 |
-
so rapidly.
|
| 27 |
-
- '[For a clickable image, click here](http://futurism.com/thisweekinscience)
|
| 28 |
|
| 29 |
|
| 30 |
-
|
| 31 |
-
|
| 32 |
-
|
| 33 |
-
_
|
| 34 |
-
|
| 35 |
-
|
| 36 |
-
Sources | Reddit
|
| 37 |
-
|
| 38 |
-
--- | ---
|
| 39 |
|
| 40 |
-
|
| 41 |
-
| [Reddit](https://www.reddit.com/r/science/comments/3jypyf/researchers_find_132_billion_yearold_galaxy_in/)
|
| 42 |
|
| 43 |
-
|
| 44 |
-
| [Reddit](https://www.reddit.com/r/technology/comments/3kj8pf/patient_receives_3dprinted_titanium_sternum_and/?ref=search_posts)
|
| 45 |
|
| 46 |
-
|
| 47 |
-
[Reddit](https://www.reddit.com/r/worldnews/comments/3kcsg5/china_to_explore_dark_side_of_the_moon_china_has/)
|
| 48 |
|
| 49 |
-
|
| 50 |
-
| [Reddit](https://www.reddit.com/r/EverythingScience/comments/3krt22/this_giant_rugby_ball_contains_a_new_chemical/)
|
| 51 |
|
| 52 |
-
|
| 53 |
-
| [Reddit](https://www.reddit.com/r/science/comments/3jum8c/astronomers_have_developed_a_new_highly_accurate/)
|
| 54 |
|
| 55 |
-
|
| 56 |
-
|
|
|
|
|
|
|
| 57 |
|
| 58 |
-
|
| 59 |
-
| [Reddit](https://www.reddit.com/r/EverythingScience/comments/3jzjlm/surprising_giant_ringlike_structure_in_the/)
|
| 60 |
|
| 61 |
-
[Recoded Cell Factories](http://m.phys.org/news/2015-09-recoded-cells-factories-proteins.html)
|
| 62 |
-
| [Reddit](https://www.reddit.com/r/EverythingScience/comments/3krux3/researchers_transform_recoded_cells_into/)'
|
| 63 |
-
pipeline_tag: sentence-similarity
|
| 64 |
-
library_name: sentence-transformers
|
| 65 |
-
---
|
| 66 |
|
| 67 |
# SentenceTransformer based on sentence-transformers/all-mpnet-base-v2
|
| 68 |
|
|
|
|
| 8 |
- dataset_size:4615
|
| 9 |
- loss:TripletLoss
|
| 10 |
base_model: sentence-transformers/all-mpnet-base-v2
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 11 |
|
| 12 |
|
| 13 |
+
---
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 14 |
|
| 15 |
+
## Model Description
|
|
|
|
| 16 |
|
| 17 |
+
This model is trained on Reddit posts from mental health discussion communities and is specifically designed for **semantic similarity tasks** between the **21 items of the Beck Depression Inventory-II (BDI-II)** and Reddit posts.
|
|
|
|
| 18 |
|
| 19 |
+
The BDI-II is a widely-used clinical assessment tool consisting of 21 items that measure symptoms and attitudes associated with depression, including hopelessness, guilt, fatigue, sleep disturbances, loss of interest, and suicidal thoughts. This model maps both BDI-II items and Reddit posts into a shared 768-dimensional dense vector space, enabling the computation of semantic similarity between clinical depression indicators and user-generated mental health narratives.
|
|
|
|
| 20 |
|
| 21 |
+
### Use Cases
|
|
|
|
| 22 |
|
| 23 |
+
The primary application of this model is **information retrieval**: given a BDI-II item as a query, the model can retrieve the most semantically relevant Reddit posts that express similar depressive symptoms or experiences. This capability is valuable for:
|
|
|
|
| 24 |
|
| 25 |
+
- **Clinical research**: Identifying real-world expressions of specific depression symptoms in social media data
|
| 26 |
+
- **Mental health screening**: Matching user posts to clinical depression indicators for early detection
|
| 27 |
+
- **Dataset construction**: Building training corpora by retrieving posts that align with established psychological assessment frameworks
|
| 28 |
+
- **Symptom analysis**: Understanding how individuals naturally express clinical depression symptoms in online communities
|
| 29 |
|
| 30 |
+
The model leverages the tendency of individuals to express mental health concerns more openly on social media platforms compared to traditional clinical settings, making it particularly suitable for pre-screening and wellness monitoring applications.[6][5]
|
|
|
|
| 31 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 32 |
|
| 33 |
# SentenceTransformer based on sentence-transformers/all-mpnet-base-v2
|
| 34 |
|